Brazilian children’s quality of life during the COVID-19 pandemic: analysis of contextual factors and dimensions

ABSTRACT Objective: The aim of this study was to investigate the contextual factors associated with the quality of life (QOL) of Brazilian children aged 0–12 years during the strict period of social isolation. Methods: This observational cross-sectional study was conducted between July and September 2020 using an online questionnaire on QOL-related family factors and the Pediatric Quality of Life Inventory (PedsQL™). Results were analyzed by multinomial logistic regression analysis. Results: The sample had 849 children, mostly from the South Region of Brazil (75%), white (83%), with typical development (79%), sedentary (68%), using screen (85%) for >3 h/day (44%). Their mothers were their main caregivers (90%). The following variables were significantly associated with high scores of QOL: typical health status (OR 2.38; 95%CI 1.60–3.55; screen time ≤2 h/day (OR 1.62; 95%CI 1.17–2.24); social distancing considered as “easy” (OR 1.67; 95%CI 1.20–2.32), and stimulation of the child by the family (OR 1.93; 95%CI 1.08–3.45). Conclusions: This study indicates that the family context can influence children’s QOL, especially during the COVID-19 pandemic and home environment reorganization.


INTRODUCTION
The COVID-19 pandemic began in Asia and quickly caused more than 5 million deaths worldwide. 1Many restriction measures were adopted to control the virus, particularly social distancing, 2 leading to deep social changes. 3In Brazil, the first case was detected on February 26, 2020, and social distancing reached its peak (62.2%) in March 2020 -a critical moment of the pandemic, 4 with many cases and deaths. 5Social distancing remained at 35-50% between April and September, 6 the period when this research, the so-called #CRIANCAEMCASA.(#CHILDRENATHOME), was implemented.
Brazil is a continent-sized country, with great diversity and inequality, 7 making it even more complex to manage the pandemic.Furthermore, there were no coordinated actions between the federal government and the states and municipalities, which took their own measures to minimize spreading of virus. 8lthough children were the least affected by COVID-19, they were likewise impacted by the pandemic. 9Health services were changed and interrupted, classes were canceled and replaced with remote teaching, social interaction with peers was restricted, and families started working from home, lost their jobs, and/ or faced financial and health difficulties, 10 resulting in a critical development phase for children due to their neuroplasticity. 2ossible health risks include both the virus itself 11 and the pandemic from a broader biopsychosocial (BPS) perspective, which considers social and psychological factors as well. 12The health status can be verified through quality-of-life (QOL) indicators 13 regarding functions and structures, activities and participation, and contextual factors, according to the International Classification of Functioning, Disability, and Health (ICF), 14 and related social determinants. 3onsidering the social transformations and restrictions imposed by the pandemic, this research aimed to investigate the greatest risk and protection contextual factors associated with 0-to 12-year-old Brazilian children's QOL, following a BPS model, at the peak social distancing during the COVID-19 pandemic.

METHOD
T h e r e s e a r c h , c a l l e d # C R I A N C A E M C A S A (#CHILDRENATHOME), followed human research ethics according to Resolution 466/12 of the National Health Council (Brazil) and was approved by the Research Ethics Committee of Federal University of Paraná under CAAE no.32679520.4.0000.0102(evaluation report no.4.146.615).
The research followed the recommendations in Strengthening the Reporting of Observational Studies in Epidemiology (STROBE Statement) 15 for cross-sectional design and convenience samples.The assessment instruments were systematized according to the ICF BPS model 14 to investigate QOL outcomes and associated risk and protective contextual factors.The assessment instruments, questionnaire, and Pediatric Quality of Life Inventory (PedsQL™) were standardized regarding health status in functioning dimensions (functions, structures, activities, and participation) and contextual factors (environmental and personal).
The research was publicized through social media (Instagram and Facebook), WhatsApp, and e-mails to caregivers of 0-to 12-year-old Brazilian children of both sexes residing in Brazil.The sampling approach used for this research was the stratified random sampling plan, with strata defined by age group and Brazilian state, with an acceptable 5% margin of error and 95% confidence level, which indicated the need for 385 responses nationwide.
Research forms included a questionnaire developed by the researchers with general questions on identification, the region in Brazil, sex, race, age, respondents' data (children's caregivers), children's health condition (typical/healthy, respiratory diseases, disabilities, COVID-19), healthcare (public, private, or both), home environment (type of housing, basic sanitation/sewage, water supply, paved street), socioeconomic (family income, government welfare, children's main caregiver's/parents' employability), educational situation (grade in school, daycare/school attendance), stimulation received by family (games or educational activities carried out with the child), media use (screen time and type), life habits (physical activity), and social distancing during the COVID-19 pandemic (binary response: easy or difficult).They were used in all age groups to determine risk or preventive factors associated with QOL.
PedsQL™ was used online with permission of the Mapi Research Trust (http://www.mapi-trust.org)to analyze QOL outcomes.It is validated for both interview and online use 16 and reliable, 17 in the versions for 1-to 12-month-and 13to 24-month-old babies 17 and 2-to 12-year-old children.The PedsQL™ (Version 4.0 Short Form (SF15) -Portuguese [Brazil]) addresses toddlers (2-4 years old), 18 small children (5-7 years old), and children (8-12 years old). 18All questionnaires are of low cost and take about 5 min to answer; 18 they were made available online to the children's caregivers, who were instructed to answer the questions considering the previous month.The instruments assess QOL with age-specific questions 3 Rev Paul Pediatr. 2025;43:e2023175 RPPed in the following dimensions: physical functioning (PF), emotional functioning (EF), social functioning (SF), and cognitive functioning (CF) or school functioning (ScF), with a total score.Physical symptoms (PS) are an additional dimension for children under 2 years old.ScF questions accepted home tasks and activities, given the social distancing imposed by the pandemic.
The answers follow a five-level Likert scale 16 for conditions and/or problems: (0=never; 1=almost never; 2=sometimes; 3=often; and 4=almost always).After being scored, the items are linearly transposed to an inverted scale from 0 to 100 (0=100, 1=75, 2=50, 3=25, and 4=0) to calculate each dimension's mean scores. 18Then, the physical health summary (PhyHS -encompassing PF [for all ages] and PS [for babies]) and psychosocial health summary (PsyHS -calculated with the mean of EF, SF, and CF or ScF) were calculated. 19edsQL™ for 1-to 12-month-old babies included this age group and those under 1 month old.In data analysis, CF/ScF were considered equivalent to compare dimensions and establish the sample's total score, encompassing all age groups.The age groups were organized as follows: 0-12 months; 13-23 months; 2-4 years; 5-7 years; 8-12 years; and all ages together (0-12 years).The total score was obtained from the mean of the PhyHS and PsyHS.PedsQL™ does not have a normative 0 to 100 QOL score -higher scores indicate better QOL. 18irst, a study pilot was made for adjustments, resulting in specific forms for each age group, made available in Linktree.The researchers publicized this research through social media (Instagram, Facebook) in a profile created specifically for it, and through WhatsApp to other researchers and possible known participants that might help publicize it to others; hence, the participants helped pass on the link to the research (snowball) to other potential participants.Moreover, the research was shared via available institutional e-mail to health researchers and program coordinators nationwide.
The link to the research first led to an online informed consent form.Those who agreed to participate answered the questionnaire in Google Forms between July and September 2020.
Regarding QOL and risk/protective factors, the sample was classified into three groups, based on PedsQL™ total score for all ages and z-score, namely, 0=sample's mean score ±1 standard deviation (SD) (medium); +1=above reference (high); and -1=below reference (low).One SD in relation to the sample has already been used as a reference cutoff in this scale. 20ociodemographic and environmental variables were organized, grouped into two categories, and analyzed concerning the outcome variable (QOL/PedsQL™) with a multinomial logistic regression model in Statistica ® , version 7. Variables scoring >90% in a single category were excluded from the model due to their low discriminatory potential.The relationship between these variables was measured by chi-square test, and significant variables were included in the model, considering only the main effects.There was no interaction with independent variables, given the loss of sample power because of the complex interactions.No multicollinearity problem for the adjustments was identified.Odds ratios were calculated to estimate the associated values between variables of interest and the outcome variable (QOL).

RESULTS
The survey forms were accessed, through Linktree control, approximately 5000 times and, excluding repeated responses, a total of 849 valid responses, with a response rate of 17%, were recorded.
Figure 1 shows data on the children's health status, activity and participation, and personal and environmental contextual factors related to the investigated children (n=849) and on the caregivers' main characteristics.Tables 1 and 2 describe, per age group and all ages combined, variables in the regression model (Tables 3 and 4) significant to identify risk/protective factors and/or relevant to explain the findings.
Responses encompassed all age groups and the five regions of the country (South: 75%).Most children were white (83%) and typically healthy (79%).Most healthcare was from the public Unified Health System (SUS, in Portuguese) (56%).Positive COVID-19 results were reported by 3% of respondents and 1% of children.Almost 74% of them attended school/daycare before the pandemic, during which most (82%) were on remote teaching.Most caregivers (57%) and children (96%) stayed home during the research period, which 73% of the sample considered difficult.
Tables 2 and 3 show the details of important variables in the regression model, associated with QOL per age group.It also presents variables that, though not identified through the model (media use, type of media, physical activities), showed evidence (Lin et al., 2020) of relationships with sedentarism and functioning.
Most children routinely used media at home (85%)mostly mobile phones (73%) and television (66%) -for more than 3 h/day (44%).In the observation per age range, the older the children, the more they used different media and for longer (Table 1).
Concerning physical activity (Table 2), most children (68%) were sedentary (0-12 years); children above 5 years old were physically active more often.As for those who were physically active (32%), most of them (51%) were so for 30 minutes, more than three times a week (33%).

DISCUSSION
Based on the total reference score and QOL categories, 16% of the children had a "low" score.Contextual factors were analyzed for the whole sample (0-12 years) and per age group.
In PedsQL™ analysis, PhyHS (85±16) was higher than PsyHS (73±20) in 0-to 12-year-old children and each age group.The scale validation process identified similar PhyHS and PsyHS values in 2-16 years (84±20 and 81±15, respectively). 20The discussion considered each PhyHS and PsyHS dimensions and the total score used to analyze the associated contextual factors.
Age group comparisons also revealed that children aged 5-7 years and 8-12 years had the worst total QOL scores (72±14; 70±15), suggesting that the pandemic impacted more of this age range's QOL.Scores were higher in PF (>80) in all ages-except for 8-12 years (77±20), which are near those found in a previous study 18 in 2-to 18-year-old Brazilian children with pathologies (76±22.7),while healthy children had higher scores (95.9±5.8).However, this validation study did not report each age group's specific values, limiting comparisons with the present study.
Lower ScF and EF values in 5-7 and 8-12 years are like the main values found in Portuguese children before the pandemic. 22nterestingly, 8-to 12-year-old children had lower QOL scores than others-also below the reference QOL mean (80.9) suggested by Ow and Mayo 13 in a study that verified values for children older than 5 years from various countries.However, the values were similar to those of a 2014 study 22  Furthermore, puberty sets differences in well-being, as QOL is influenced by sex and age. 13This was also found in a study conducted in Indonesia. 2Hence, Brazilian results indicate that 5-7 and 8-12-year-old children -age groups with intense social and school relationships -have lower QOL scores.Although sex differences were not comparatively analyzed in the present study, sex was not a significant variable in this model.
ScF and EF values were similar to mean scores found in Brazilian children in 2014, 22 although EF scores were lower than in other QOL dimensions.Previous study 24 identified anxiety and depression in Brazilian children aged 6 to almost 12 years, possibly because of stress from the pandemic and the fewer physical activity opportunities.Being less physically active has been previously reported as a predisposing factor to emotional problems. 25Physical activities could help minimize these problems, 26 especially in children with scores below the mean -"low" scores in the present study.
Lower ScF scores in 5-7 and 8-12 years make sense, as in-person classes were canceled and replaced with remote teaching.This may point to future learning difficulties, particularly in children with lower scores and therefore at greater risk.
Sedentarism was identified in children isolated at home, which, in combination with media use and high screen time, resulted in their low percentages of physical activity.Most children used media, especially mobile phones, and television, for more than 3 h/day, which agrees with reports in other studies. 27All groups used media, progressively increasing with age.Despite the screen time in school-age children (which may be ascribed to school activities), daily usage time (>3 h) is greater than those recommended by the Brazilian Society of Pediatrics 28 -for all ages (<2 years: no use; 2-5 years: up to 1 h/day; 6-10 years: 1-2 h/ day; ≥11 years: 2-3 h/day).
These results agree with another study on Brazilian children under 13 years old (March to April 2020), which identified that staying at home during the pandemic reduced physical activity by 46% and increased screen use by 38%. 27This is similar to what has been found in Brazilian adults, 29 and Indonesian 2 and Chinese children and adolescents. 30Considering the limited interaction with other children -particularly as most families had only one child at home-greater contact with adults may explain such sedentarism and greater screen time.
Although the pandemic increased family activities, some studies 24,31 identified that playing without physical activity predominated, often accompanied by media use.The relationship between less screen time and better QOL outcomes calls attention to overall consequences for children's health and well-being.Evidence indicates that excessive use may have emotional and/or behavioral consequences for children. 32iven the increasing media use at all ages, 33 this situation calls for attentive follow-up.Besides screen time, the quality of use must be further investigated to provide more precise guidance on specific media use per age group and its risks and/or benefits.
Thus, screen time must also be addressed concerning SF and physical activity.Less screen time may enable greater social interaction, even when limited to the family -which was a protective factor for children's QOL in this study.Inversely, high screen time tends to diminish active play, impairing children's development and well-being.
The typical health status may be related to caregivers' overall perception of children's well-being, which encompasses various QOL dimensions.Better QOL scores were found in typically developed babies than in those at risk/delay 21,34 -and higher scores reflect a better QOL, 16 as there are fewer changes in health status.
Research children's main caregivers were women, young, married, and their mothers, who took 40% of their daily time -2.8 times greater than the fathers' -caring for the children.Mothers' greater participation in research on children's health 35,36 confirms their role as the main caregiver.The less time fathers spent with children was a risk factor for 0-12 and 2-4-yearold children's QOL, as well as paternal absence in 0-12 years and 13-23 months old.
These data corroborate both the women's being the greatest workforce in childcare and household chores 37 and the increased risk to children due to paternal absence. 38ot attending a daycare center was a protective factor for those aged 13-23 months.These data must be cautiously interpreted, as only 4.5% of the 0-to 12-month-old children attended daycare before the pandemic, which may justify the almost null OR values; while 45% of the 13-to 23-month-old ones did so -and during the pandemic, these babies remained at home.However, the literature reports both negative 39 and positive daycare influences 40 on small children who attend daycare centers.
Protective social interaction factors for QOL corroborates health analysis in the ICF BPS model.It addresses environmental influences, 41 including parental relationships and interactions, 41 agreeing with QOL multidimensionality.These factors Rev Paul Pediatr. 2025;43:e2023175 RPPed had to be adjusted during social distancing, which may have long-term consequences for children's neuropsychomotor development, as the quality of the environment the children could explore was limited 42 and the exposure to situations of risk and violence increased. 43espite the high screen use and less physical activity, most families stimulated children at home, which was a protective factor for better QOL scores (0-12 years), recognizing the positive effects of parental stimulation. 44Stimulation opportunities at home are known to be associated with neuropsychomotor development, which may influence the QOL. 45emote teaching during the pandemic may have failed to reach more vulnerable populations.QOL is multidimensional, and the three Southern states -the most represented in this study -have the lowest inequality rates in the Gini index (Santa Catarina, Paraná, and Rio Grande do Sul), 7 the highest human development indices, 46 and the lowest incidence and mortality rates from COVID-19 in 2020. 7Hence, worse and more complex situations can be expected in more vulnerable populations, as Brazil has great inequalities, 7,46 including in access to media and the Internet.In 2018, about 10-16% of schoolchildren still had no access to the Internet, with differences between the states and less access in poorer ones. 47hus, this study's contextual factors associated with children's QOL may not represent Brazil as a whole.Nonetheless, considering QOL as a health indicator for Brazilian children during the pandemic, the differential of this research is the BPS analysis, with validated, quick, low-cost instruments 21,48 -which may identify associated factors faster to plan future measures on both the individual (children in their families) and macro levels (pediatric healthcare management), having a multiprofessional team use family-centered intervention programs 49 and instruments such as PedsQL ® .
Some limitations of the study need to be pointed out.The results should not be extrapolated to the entire Brazilian population, considering that, because of the sample size and due to the distancing measures and the online nature of the survey, the respondents do not represent the entire diversity of the country.Furthermore, those interested in the research may possibly be the ones with the greatest interest and even the most experience in childcare.With regard to the territory, because Brazil is a continental country, with vast geographical, social, and economic diversity, even in the pandemic, the COVID-19 control measures varied greatly among the different regions of Brazil, limiting generalizations.Also, the QOL, as stated by PedsQL™, reflects the perception of caregivers (and not children's perception), depending on their perspective and commitment to a true response possible.
The present study identified that, during a period of social distancing due to the COVID-19 pandemic, the protective factors associated with Brazilian children's QOL were the typical health condition, less exposure to screens (screen time ≤2 h/day), social distancing considered easy" by families, and receiving stimulus (games or educational activities carried out with the child) from the family at home.
applicable; m: months; y: years.*Up to 23 months only; **Average value of physical and psychosocial health summaries.
on Portuguese children.These divergences reinforce the need for populational Rev Paul Pediatr. 2025;43:e2023175 RPPed investigations addressing each country's social needs to compare and establish reference scores.
PA: physical activity.Significant variables to the regression model.*Percentages calculated based on the number of children who used media/ were physically active.Rev Paul Pediatr. 2025;43:e2023175 RPPed

Table 3 .
Variables of the regression model associated with the quality of life -PedsQL™ (n=849).

Table 4 .
Variables of the regression model associated with the quality of life -PedsQL™ per age range (n=849).